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Research and Development study of the comprehensive system for evaluating and elaborating students' deeper learning in the course of mathematics.

Research Project

Project/Area Number 20H01720
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 09070:Educational technology-related
Research InstitutionNagoya University

Principal Investigator

Mitsunaga Haruhiko  名古屋大学, 教育発達科学研究科, 准教授 (70742295)

Co-Investigator(Kenkyū-buntansha) 孫 媛  国立情報学研究所, 情報社会相関研究系, 准教授 (00249939)
鈴木 雅之  横浜国立大学, 教育学部, 准教授 (00708703)
山口 一大  筑波大学, 人間系, 助教 (50826675)
植阪 友理  東京大学, 大学院教育学研究科(教育学部), 准教授 (60610219)
Project Period (FY) 2020-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥17,290,000 (Direct Cost: ¥13,300,000、Indirect Cost: ¥3,990,000)
Fiscal Year 2023: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2022: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2021: ¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2020: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Keywords認知診断モデル / 深い学び / 授業改善 / 算数教育 / クラスルームテスト / 学力調査 / 指導改善 / 授業評価 / 数学教育 / 初等教育 / 学力評価
Outline of Research at the Start

2020年度より全面施行される新学習指導要領では「深い学び」の重要性が指摘されている。一方,教育測定の分野では,認知診断モデルと呼ばれる心理モデルを応用し,認知過程の処理水準の深さ,すなわち学びの深さを測定しようとする研究が行われてきた。本研究課題では日本の小中学生の算数・数学を題材に,認知診断モデルに基づき,学びの処理水準を定量的に測るための方法を開発し,その結果を授業の改善に生かすための具体策を提案することを目的とする。学びの深さを意識したカリキュラム実践の進展に寄与することが期待される。

Outline of Final Research Achievements

In recent years, many practices to reveal students’ achievement of certain fields using “Cognitive Diagnostic Model (CDM)” have been carried out in Japan. This study aims to apply CDM analysis to classroom test data on the mathematical course in elementary school, and to illustrate students’ “depth of learning”, which is mentioned in the field of cognitive psychology. Through the study including administrations of classroom tests and interaction with teachers, we discuss the way of interpreting indices of CDM achievement and how to use these indices to make their classroom better. Results show that it is necessary for teachers who want to enhance their classroom activity to use not only achievement indices by CDM analysis but also consideration of what the test items aim to measure in the aspects of students’ mathematical competency.

Academic Significance and Societal Importance of the Research Achievements

本研究は、これまでクラスルーム単位で行われてきた「小テスト」のような達成度確認テストにおいて、新たな観点からテスト実施の方法を提案している。本研究の提案手法により、クラスルームや学校間で共通の「学びの深さ」を測るためのテストを用いて、結果の評価手法を含めて標準化された手順で学びの深さを探ることが期待される。あわせて、従来、教員の主観によることが多かった「学びの深さ」の判断において、ある程度の大まかさで定量的評価を行おうとした研究であり、日本の教育測定分野における先駆的な研究である。また「主体的・対話的で深い学び」の実現を目指す教員に対して一つの手掛かりを提供するものである。

Report

(5 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Annual Research Report
  • 2021 Annual Research Report
  • 2020 Annual Research Report
  • Research Products

    (21 results)

All 2023 2022 2021 2020

All Journal Article (10 results) (of which Int'l Joint Research: 5 results,  Peer Reviewed: 9 results,  Open Access: 8 results) Presentation (10 results) (of which Int'l Joint Research: 6 results) Book (1 results)

  • [Journal Article] Diagnosing the depth of understanding using cognitive diagnostic models and their application to a regular test: Examining the applicability of cognitive diagnostic models with a Q-matrix specified through qualitative and quantitative procedures2023

    • Author(s)
      佐宗 駿、岡 元紀、植阪 友理
    • Journal Title

      Cognitive Studies: Bulletin of the Japanese Cognitive Science Society

      Volume: 30 Issue: 4 Pages: 515-530

    • DOI

      10.11225/cs.2023.057

    • ISSN
      1341-7924, 1881-5995
    • Year and Date
      2023-12-01
    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Current Status of Open Science and Statistical Analysis in <i>The Japanese Journal of Educational Psychology</i>:2023

    • Author(s)
      山口 一大
    • Journal Title

      The Annual Report of Educational Psychology in Japan

      Volume: 62 Issue: 0 Pages: 143-164

    • DOI

      10.5926/arepj.62.143

    • ISSN
      0452-9650, 2186-3091
    • Year and Date
      2023-03-30
    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Bayesian Analysis Methods for Two-Level Diagnosis Classification Models2023

    • Author(s)
      Yamaguchi Kazuhiro
    • Journal Title

      Journal of Educational and Behavioral Statistics

      Volume: 48 Issue: 6 Pages: 773-809

    • DOI

      10.3102/10769986231173594

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Variational Bayes inference for hidden Markov diagnostic classification models2023

    • Author(s)
      Yamaguchi Kazuhiro、Martinez Alfonso J.
    • Journal Title

      British Journal of Mathematical and Statistical Psychology

      Volume: 77 Issue: 1 Pages: 55-79

    • DOI

      10.1111/bmsp.12308

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Bayesian estimation of test engagement behavior models with response times.2023

    • Author(s)
      Yamaguchi, K., & Fujita, K.
    • Journal Title

      Tsukuba psychological research

      Volume: 61 Pages: 75-87

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Direct Estimation of Diagnostic Classification Model Attribute Mastery Profiles via a Collapsed Gibbs Sampling Algorithm2022

    • Author(s)
      Yamaguchi Kazuhiro、Templin Jonathan
    • Journal Title

      Psychometrika

      Volume: Online Ahead of Print Issue: 4 Pages: 1390-1421

    • DOI

      10.1007/s11336-022-09857-7

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Review of recent developments of parameter estimation methods in item response theory models with focus on studies reported in Psychometrika2022

    • Author(s)
      山口 一大
    • Journal Title

      Japanese Journal for Research on Testing

      Volume: 18 Issue: 1 Pages: 103-131

    • DOI

      10.24690/jart.18.1_103

    • ISSN
      1880-9618, 2433-7447
    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] メタ認知と学力の関係2021

    • Author(s)
      鈴木雅之
    • Journal Title

      指導と評価

      Volume: 67(9) Pages: 6-8

    • Related Report
      2021 Annual Research Report
  • [Journal Article] A Gibbs Sampling Algorithm with Monotonicity Constraints for Diagnostic Classification Models2021

    • Author(s)
      Kazuhiro Yamaguchi, and Jonathan Templin
    • Journal Title

      Journal of Classification

      Volume: 39 Issue: 1 Pages: 24-54

    • DOI

      10.1007/s00357-021-09392-7

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Variational Bayesian inference for the multiple-choice DINA model2020

    • Author(s)
      Yamaguchi, K.
    • Journal Title

      Behaviormetrika

      Volume: 7 Issue: 1 Pages: 159-187

    • DOI

      10.1007/s41237-020-00104-w

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed
  • [Presentation] Development of assessment tools for depth of understanding quantitatively with cognitive diagnostic models.2023

    • Author(s)
      Saso, S., Oka, M., & Uesaka, Y.
    • Organizer
      Future of Information and Communication Conference (FICC)
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Statistically gauging vital subcomponents of diagrammatic competency2023

    • Author(s)
      Saso, S., & Uesaka, Y.
    • Organizer
      The European Association for Research on Learning and Instruction (EARLI)
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Advancing Educational Content Classification via Reinforcement Learning-Integrated Bloom’s Taxonomy2023

    • Author(s)
      Thanveer Shaik, Xiaohui Tao, Lin Li, Christopher Dann, Yuan Sun and Yi Sun
    • Organizer
      the 3rd International Conference on Digital Society and Intelligent Systems (DSinS 2023), Chengdu, China
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Adaptive Learning in Digital Age: Some Key Technologies2021

    • Author(s)
      Yuan Sun
    • Organizer
      2nd International Conference on Artificial Intelligence in Education Technology (AIET 2021)
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research
  • [Presentation] How can we statistically gauge students’ deep understanding from high school regular tests?2021

    • Author(s)
      Saso, S., Oka, M., & Uesaka, Y.
    • Organizer
      Junior Researchers of European Association for Research on Learning and Instruction (JURE)
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Parallelized variational Bayesian algorithm for the polytomous-attribute saturated diagnostic classification model.2021

    • Author(s)
      Oka, M., Saso, S., & Okada, K.
    • Organizer
      World Meeting of the International Society for Bayesian Analysis (ISBA) 2021
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 「主体的に学習に取り組む態度」をいかにして育成し,評価するか:高校数学における定期試験のフィードバック方法に着目して2021

    • Author(s)
      秋澤武志・植阪友理・佐宗駿
    • Organizer
      日本教育工学会2021年秋季全国大会 (第39回大会)
    • Related Report
      2021 Annual Research Report
  • [Presentation] 深い学びの評価方法の提案と定期テストへの応用―認知診断モデルの応用可能性と教師の反応―2021

    • Author(s)
      佐宗駿・岡元紀・植阪友理(2021)
    • Organizer
      日本教育工学会2021年春全国大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] 図表活用力を定期試験から定量的に捉えるには? -認知診断モデルを用いた資質・能力の実証的解析-2021

    • Author(s)
      佐宗駿・植阪友理・秋澤武志
    • Organizer
      日本教育心理学会第63回総会
    • Related Report
      2021 Annual Research Report
  • [Presentation] 認知診断モデルを通じた深い理解の実証的解析 -大規模学力調査を用いた分析と従来の観点との比較-2021

    • Author(s)
      佐宗駿・岡元紀・植阪友理
    • Organizer
      日本テスト学会第19回大会
    • Related Report
      2021 Annual Research Report
  • [Book] 学校現場で役立つ 教育心理学―教師をめざす人のために―2021

    • Author(s)
      鈴木雅之
    • Total Pages
      17
    • Publisher
      北大路書房
    • Related Report
      2021 Annual Research Report

URL: 

Published: 2020-04-28   Modified: 2025-01-30  

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